Users are increasingly utilizing electronic devices to obtain various types of information. For example, a user wanting to obtain information about a book can capture an image of the cover of the book and upload that image to a book identification service for analysis. In many cases, the cover image will be matched against a set of two-dimensional images including views of objects from a particular orientation. While books are relatively easy to match, as a user will generally capture an image of the cover of the book with the cover relatively centered and upright in the image, other objects are not as straightforward. For example, an object such as a pair of boots might be imaged from several different orientations, with many of those orientations not matching the orientation of the stored image for that type or style of boot. Similarly, objects such as computers typically have images stored that show the computer with the screen in one orientation, which can have a significantly different shape than when computer screen is in a different orientation. Further, single two-dimensional images typically do not provide any information about dimension or scale, such that an image matching algorithm might not be able to determine the difference between a model airplane and the corresponding actual airplane. These differences in orientation, size, and shape, among other such differences, can prevent accurate matches from being located for various images captured by a user.